Systems and methods for trading a trade list in financial markets

ABSTRACT

Systems and methods are provided for maintaining neutrality while trading a list of securities using an algorithmic trading facility coupled with at least one destination. This destination includes at least one alternative trading system (ATS). This facility is coupled, via an electronic data network, to a plurality of trading clients, and configured to receive a trade request to trade a list of securities from a trading client. This request includes user defined trading constraints that are used to generate and transmit trade orders to at least one ATS. The orders are transmitted based on trading data related to the destinations, the trade list, and the trading constraints. The facility can identify each executed trade corresponding to the trade orders and calculate a trade imbalance. The facility can determine whether the trade imbalance exceeds the trading constraints, and reallocate one or more of said submitted orders based on this determination.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 13/330,017, filed Dec. 19, 2011, which is acontinuation of U.S. patent application Ser. No. 12/044,685, filed Mar.7, 2008, now U.S. Pat. No. 8,082,204, issued Dec. 20, 2011, which is anon-provisional application of U.S. Patent Application No. 60/905,317,filed Mar. 7, 2007, the contents of each of which are incorporatedherein in their entirety.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates generally to systems and methods fortrading a trade list in non-displayed markets. In particular, thepresent invention relates to systems and methods for maintainingconstraints, such as dollar or sector neutrality, when tradingsecurities, found in a trade list or portfolio, in alternative tradingsystems.

Description of the Related Art

Generally, in the financial trading industry, there are two types ofavailable destinations for execution of orders to trade securities:“displayed” and “non-displayed.” At a displayed destination, informationrelating to BUY orders (bids) and to SELL orders (offers) is madeavailable to interested parties. By contrast, BUY and SELL orders sentto non-displayed destinations are not made available to the public, andare instead kept hidden. The lack of disclosure found in non-displayedtrading forums provides both benefits and drawbacks, as furtherdiscussed below.

The NYSE, NASDAQ, and ECNs are examples of displayed destinations, alsocalled the “open markets.” These destinations publish, by subscriptionor otherwise, data related to BUY and SELL orders, e.g., “level 2” dataavailable at each trading destination. This published data can beelectronically transmitted to subscribers, and be displayed using agraphical user interface in combination with a display device, such as adesktop computer.

Non-displayed destinations are generally known as alternative tradingsystems or ATSs. Because BUY and SELL order information in ATSs is kepthidden, these trading forums are attractive destinations for traders whodesire minimal information leakage about their orders. By minimizing theinformation leakage, market impact can be minimized, at least, oravoided, at best. Institutional traders often trade large quantities ofshares, commonly called “blocks”, and information leakage can result inprice movement that may have a dramatic affect on the trader's overallreturn.

For example, if a trader submitted a BUY order for 100,000 shares of IBMto a displayed destination, information about this BUY order would beavailable to everyone subscribing to the corresponding market data.Sellers armed with knowledge of the submitted BUY order would be awareof the high demand for IBM and will submit SELL orders for IBM at anincreased price. As a result, upward pressure is placed on the IBM stockprice. Conversely, if the same BUY order had been submitted at an ATS,the order information would have been hidden, and any risk of upwardpressure resulting from the BUY order information would have beenalleviated.

ATSs generally differ from displayed markets with respect to tradeexecution price. In particular, unlike displayed destinations, when amatch occurs at an ATS between BUY and SELL orders for the samesecurity, the ATS typically sets an execution price for that match thatis derived from current prices displayed in the open markets. In someATSs, such as ITG's POSIT, the execution price for a match is themidpoint price of the displayed market bid and ask.

Unfortunately, ATSs suffer from some disadvantages because of theirhidden or “dark” nature. One disadvantage is that the liquidityavailable at ATSs is typically smaller than the liquidity available atdisplayed destinations. However, as described above, the non-displayedliquidity of ATSs is valuable to institutional investors due to thereduced risk of information leakage.

Compounding the smaller liquidity, is the fact that traders cannot seethe BUY and SELL orders available in the ATSs. As a result, there is noguarantee of a trader completely or partially filling a BUY or SELLorder submitted to an ATS. Thus, the risk of no execution or partialexecutions always exists when trading in ATSs.

ATSs have the disadvantage that their liquidity is not continuous. Thatis, the liquidity found at an ATS during one trading period is notnecessarily found during any other trading period. Further, theliquidity that exists at an ATS is not necessarily consistent eventhroughout the trading time period. Moreover, liquidity between ATSsvaries, and while one ATS might have high liquidity for a particularstock, a different ATS might simultaneously have low liquidity for thesame stock.

Some ATSs have minimum size requirements that restrict when an order canbe submitted to the ATS. The bigger the minimum size limitation, thelarger the dollar commitment to that ATS becomes. Thus, a trader thatwants to trade at a particular ATS that has a high minimum sizerequirement may be forced to concentrate their trade orders at that oneATS, rather than a variety of ATSs having smaller minimum sizerequirements or no size requirements.

It is not possible for a trader to force the execution of an order at anATS if the liquidity is simply not present. Trying to force an execution(by crossing the bid-ask spread) is a capability in the open marketsthat causes information leakage.

Many investment managers maintain portfolios that are both long andshort (i.e., different securities are bought and sold in the sameportfolio). The purpose of such a strategy is to hedge market risk andcapture relative stock specific returns. In order to keep these types ofportfolios fairly risk neutral, it is important to trade them at aspecified rate, consistent with the overall composition of theportfolio. Typically, this rate is 1:1, which means SELLs and BUYsshould be executing at the same rate dollar wise (i.e., “dollarneutrality”). When SELLs and BUYs execute at the same rate, the tradingis dollar neutral. However, there may be times when a trader desires adifferent rate of execution.

Dollar neutrality during trading is also important to managers ofportfolios that contain only long positions (i.e., long-onlyportfolios). When long-only portfolios are rebalanced, the resultingtrade lists are typically a mixture of BUY and SELL trades, containingstocks the trader wishes to increase and decrease positions in.Maintaining dollar neutrality throughout the duration of trading helpsreduce a portfolio or trade list's exposure to stock price volatility.As prices generally rise, unfilled BUY orders will become more expensiveto execute, while unfilled SELL orders will be more valuable. Thus,value lost on one side of the trade list is hedged by the change invalue of the list's other side.

Dollar neutrality is difficult to achieve when trading in ATSs for atleast the above-described reasons. One way to control dollar neutrality,and other properties of a trade list, while trading in one or more ATSsis to submit a limited number of small orders to the various ATSs. Theorders can be sized in such a way that when filled, the list'sproperties, for example dollar neutrality, are maintained. However, thistechnique limits the exposure of the trader's orders to the hiddenliquidity available at the ATSs. Therefore, this technique isundesirable because it forces a trader to sacrifice possible executionsin order to maintain a trade list's neutral characteristics.

Similar to dollar neutrality is the concept of “sector neutrality.” Inthe case of sector neutrality, a trader desires to maintain dollarneutrality, as described above, on a sector level. In other words, ifthe list is broken down into many sub-lists—one list for eachsector—then sector neutrality is equivalent to applying dollarneutrality at the sub-list level. Sectors maybe broken down by industry,for example agricultural or automotive.

For displayed destinations, i.e., open markets, algorithms exist fortaking a long-short portfolio, and ensuring that the execution ratebetween the BUYs and SELLs are within a specified tolerance. This iseasy because the markets are displayed. If one side, either BUY or SELL,of the portfolio happens to be over executing, algorithms can adjust therate of execution by canceling out trades on the side that is overexecuting. Furthermore, these algorithms have the ability to cross thebid-ask spread for the side that is executing too slowly, virtuallyensuring an execution for that side.

Additionally, in a displayed destination, a trader may utilize marketorders that will continually consume liquidity until the client order isfilled. This is possible because, in a displayed destination, currentmarket pricing and liquidity is visible. However, when trading at ATSs,it may be difficult to determine if a counter party exists for a trade,and because the liquidity at an ATS remains hidden there can be noguarantee of an execution. Furthermore, most ATSs will automaticallycross at the midpoint, thus there is no incentive for any trader toimprove their order price to attract further liquidity.

In view of the foregoing, there is a need for new and improved systemsand methods for trading trade lists or portfolios within ATSs whilemaintaining dollar neutrality and/or sector neutrality.

SUMMARY OF THE INVENTION

According to various embodiments of the present invention, a method fortrading a list of securities is provided. This method includes a step ofreceiving a request to trade a list of securities is received. Thisrequest may include user defined trading constraints. Trade orders maybe submitted to destinations including at least one alternative tradingsystem (ATS). These order submissions may be based on trading datarelated to the destinations, the trade list, and the tradingconstraints. Each executed trade from the trade orders is identified. Atrade imbalance is calculated. The trade imbalance may be based on theidentified executed trades and the trade list. It is determined if thetrade imbalance exceeds the trading constraints. One or more of thesubmitted orders may be reallocated based on the determining step.

According to various embodiments of the present invention, a system fortrading a list of securities is provided. The system includes analgorithmic trading facility coupled with at least one destination. Thisdestination includes at least one alternative trading system (ATS).Further, the algorithmic trading facility is coupled, via an electronicdata network, to a plurality of trading clients. The algorithmic tradingfacility is configured to receive a trade request to trade a list ofsecurities from a trading client. This request includes user definedtrading constraints that are used to generate and transmit trade ordersto at least one ATS. The transmitting of trade orders is based ontrading data related to the destinations, the trade list, and thetrading constraints. Further, the algorithmic trading facility canidentify each executed trade corresponding to the trade orders andcalculate a trade imbalance. The trade imbalance is based on theidentified executed trades and the trade list. Further, the algorithmictrading facility can determine whether the trade imbalance exceeds thetrading constraints, and reallocate one or more of said submitted ordersbased on this determination.

According to various embodiments of the present invention, acomputer-readable storage medium having computer executable program codestored therein for trading a list of securities is provided. Thiscomputer-readable storage medium may contain the following codedoperations. An operation for receiving a request to trade a list ofsecurities. This request may include user defined trading constraints.An operation for submitting trade orders to destinations including atleast one alternative trading system (ATS). These order submissions maybe based on trading data related to the destinations, the trade list,and the trading constraints. An operation for identifying each executedtrade from the trade orders. An operation for calculating a tradeimbalance. The trade imbalance may be based on the identified executedtrades and the trade list. An operation for determining if the tradeimbalance exceeds the trading constraints. An operation for reallocatingone or more of the submitted orders based on the determining operation.

According to various embodiments of the present invention, systems andmethods are provided that can virtually ensure that a trade list meetsconstraints, see example dollar and/or sector neutrality, whensimultaneously trading in at least one of non-displayed trade forums,such as an ATS. A plurality of trade orders can be generated andsubmitted to a plurality of ATSs simultaneously while accuratelyestimating stock liquidity using historical and real-time sampled tradedata for each stock at each ATS. Controls can be provided to monitoreach execution for the trade orders placed in the ATSs, and to rebalancethe trade lists to meet trade constraints.

According to various embodiments of the present invention, systems andmethods are provided for trading in at least one ATS while maintainingdollar and/or sector neutrality. Using historical data, the amount ofliquidity available in at least one ATS is estimated for each securityin a trade list. Based on expected liquidity, trade orders are generatedand submitted to one or more ATSs. Other trading characteristics that atrader might want to maintain include sector weights, country/regionweights, liquidity, and/or forecast risk (estimated by a risk model) inthe filled or unfilled shares.

According to other embodiments of the present invention, trade ordersare further generated based on capital imbalance (i.e., dollarneutrality) for a trade list.

According to other embodiments of the present invention, trade ordersare further generated based on capital imbalance for equities in a samesector (i.e., sector neutrality) within a trade list.

Further applications and advantages of various embodiments of thepresent invention are discussed below with reference to the drawingfigures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary system for trading a tradelist according to an embodiment of the present invention;

FIG. 2 is a flow chart of an exemplary method for trading a trade listaccording to an embodiment of the present invention;

FIG. 3 is a flow chart of an exemplary method for optimizing a tradelist according to another embodiment of the present invention;

FIG. 4 is a flow chart of an exemplary method for creating a trade listaccording to an embodiment of the present invention; and

FIG. 5 is a screen shot of a graphical user interface according to anembodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

While the present invention may be embodied in many different forms, anumber of illustrative embodiments are described herein with theunderstanding that the present disclosure is to be considered asproviding examples of the principles of the invention and such examplesare not intended to limit the invention to any specific preferredembodiments described and/or illustrated herein. The followingdescription of embodiments of the present invention utilize the definedterms and variables found below.

“Hit rate,” or “hit rate probability,” is the probability that anyliquidity (even an amount that will result in a partial execution) willbe present at a particular ATS. The hit rate for a security can bemeasured from historical and/or real-time market data for an ATS, andindicates the probability that any liquidity will be present. The hitrate of a security or type of security has been found to increase when afill in the security has recently occurred. Accordingly, real-timeanalytics can be used to determine if a complete or partial fill for aparticular stock occurred in a time period, e.g., the past T minutes,where T is a number that is either set or user defined. A conditionalhit rate can be used with or as an alternative to the hit rateprobability.

“Conditional hit rate” can be represented as equation:

conditional hit rate for stock i in ATS j=Probability of an execution ofstock i in ATS j|an execution in stock i in ATS j just occurred.

A “trade imbalance” is the total value of SELL executions (includingshorts) minus the product of a SELL-to-BUY Ratio and the total value ofBUY executions, as shown as an equation:

${{Trade}\mspace{14mu} {Imbalance}} = {{\sum\limits_{i \in {Sells}}{ExecutedValue}_{i}} - {\left( {{SELL}\text{:}{BUY\_ Ratio}*{\sum\limits_{j \in {Buys}}{ExecutedValue}_{j}}} \right).}}$

An “expected fill imbalance” is a predicted trade imbalance based on thecomposition of the trade list and on corresponding historical data. Theexpected fill imbalance can be used for a number of purposes includinggeneration of an initial set of orders and for the construction of tradelists predisposed to dollar neutrality. To determine the expectedimbalance, it is first necessary to find the expected fill value for astock. The expected fill value for a stock is the hit rate probabilitytimes the average trade size for that stock times the stock price. Theexpected fill value for a stock may be represented by the equation:

Expected Fill Value for stock i=Hit Rate for stock i*Avg TradeSize*Price of Stock i.

The expected trade imbalance for a trade list is the sum of all theSELL's expected fill sizes minus the product of the SELL-to-BUY Ratioand all the BUY's Expected fill sizes, as shown in the equation:

${{Expected}\mspace{14mu} {Trade}\mspace{14mu} {Imbalance}} = {{\sum\limits_{i \in {Sells}}{ExpectedFillValue}_{i}} - {\left( {{SELL}\text{:}{BUY\_ Ratio}*{\sum\limits_{j \in {Buys}}{ExpectedFillValue}_{j}}} \right).}}$

FIG. 1 is a block diagram illustrating salient features of a system fortrading a trade list according to an embodiment of the presentinvention. The system may include one or more client trading desktops102 that may be electronically coupled with an electronic data network104. Also coupled with the network are a plurality of trading forumsincluding, but not limited to, displayed destinations such as the NASDAQ106A, NYSE 106B, and ECNs 106C, and non-displayed destinations, such asa plurality of ATSs 108. ITG Inc., the assignee of the presentinvention, owns and operates several ATSs including POSIT, POSIT Match,and POSIT Now.

Each client 102 may be configured to transmit trade orders directly tothe destinations via the network using a FIX connection or the like.Accordingly, each client 102 may include order management system (OMS)or execution management system (EMS) facilities for creating, updating,cancelling, transmitting, and tracking trade lists, portfolios and/ororders. Commercially available OMSs and EMSs are known; for example, ITGInc., the assignee of the present invention, offers several EMS and OMSsolutions (see, www.itg.com). A trade list may include, but is notlimited to, information such as: stock symbol or name, side oftransaction (e.g., BUY or SELL), and number of shares to be traded.

An algorithmic trading facility 110 may be provided that is also coupledwith the network, and that may be configured to receive a trade request(typically comprising a trade list along with user specified tradeconstraints) from a client 102 and to effect that trade request bygenerating and transmitting a plurality of trade orders to at least oneATS. As is described in more detail below, the algorithmic tradingfacility is also configured to dynamically monitor and reallocate thetrade orders in order to satisfy trader submitted constraints, e.g., thealgorithmic trading facility 110 is configured to add, cancel, modifyand move trade orders in order to maintain a ratio of executed BUYorders and SELL orders equal to a trader selected ratio (e.g.,neutral=1).

User specified tolerances may also be included in the trader'sconstraints. For example, a trader could submit a trade list,constraints requiring that the trade list be executed a certain way(e.g., dollar neutral (i.e., SELL Value/BUY Value=1)), and constraintsspecifying the degree or range (i.e., a tolerance) that the resultingtrades can deviate from the specified ratio (i.e., 1). Moreover, thetolerance constraints can be different for BUY orders than for SELLorders. Further, a trader may set the desired dollar, sector, country,region, currency, and/or risk targets to be followed during trade listexecution. Additionally, the tolerance may be specified as a tradeimbalance, in which case, the trade imbalance result is compared to atrader's tolerance preferences when determining whether tradeconstraints have been met within the specified range. According to apreferred embodiment, the trader specifies the upper and lower bounds asa BUY minus SELL tolerance and a SELL minus BUY tolerance, respectively.

In order to achieve a trade list execution that meets user specifiedtrade constraints in ATSs, the system may continually monitor and assessexecution data for the BUY and SELL trade orders submitted to theplurality of ATSs for deviation from acceptable tolerances. For example,the algorithmic trading facility 110 can be configured to receive marketor trade data (i.e., historical and real-time) from trade datafacilities, such as, but not limited to, subscriber data feeds, trademessages, etc., and to calculate the trade imbalance of the executionsand compare the calculated trade imbalance to trade constraints. Ifthere is one side (BUY or SELL) that is over executed with total valueof executions, then orders on that side can be reallocated (e.g.,cancelled or modified) until the under executed side may catch up.

According to a preferred embodiment of the present invention, the systemis configured to cancel trade orders on an over executing side (e.g.,BUY or SELL) in the event that the user specified tolerance for thetrade constraints is close to being violated. The algorithmic tradingfacility can be configured to monitor executions on a timed basis, forexample, every 10 seconds, to determine whether the current tradeimbalance of the trade list exceeds the trader specified tolerance. Asstated above, the tolerance can be specified as a range, and the upperand lower bounds can be different.

When the imbalance is within Y %, for example 90%, of either tolerance,a mode is entered known as risk trading. During risk trading, orders arecanceled out on the side of the portfolio that is over executingrelative to the trader's preferences. This allows the lagging trade sideto catch up, and for the trade list to regain and maintain neutrality.The systems and methods exit risk trading and enter normal trading modewhen dollar neutrality is within Z %, for example 50% of the tolerance.In a preferred implementation, 0<Z<Y.

The present invention is not simply reactive—only correcting for dollarneutrality after the acceptable tolerances have been violated—rather,the present invention can proactively prevent trade constraints frombeing violated while trading in non-displayed trade destinations. Inorder to be proactive, both historical and real-time data can beutilized to estimate and predict the execution of trades that may impactthe trade list. With this market information, trade orders can begenerated and transmitted in such a way that the estimated and predictedrate of trades will meet the user specified trade constraints (e.g.,dollar and/or sector neutrality).

The estimation of “hit rates” and average trade sizes per stock per ATScan be utilized to generate and/or optimize a trade list or portfoliotrade in at least one ATS that complies with user specified tradeconstraints. By using historical sampled data, from sources such as ITGInc., the average trade size can be estimated for each security name ineach ATS. The average trade size of a stock in an ATS impacts theliquidity of that stock in that ATS. Furthermore, it is possible toestimate from historical data the probability that any liquidity (evenan amount that will result in a partial execution) will be present whentrading a particular security or type of security at a particular ATS,i.e., hit rate.

As stated above, the hit rate of a security or type of security has beendetermined to increase when a fill in the stock has recently occurred.Accordingly, the algorithmic trading facility can be configured toperform real-time analytics to determine if a fill, complete or partial,for a particular stock occurred in a time period, e.g., the past Tminutes, where T is a number that is either set or user defined. Theconditional hit rate can be used with or as an alternative to the hitrate described above.

In order to determine when tolerance levels have been, or may be,compromised, preferably, a minimum of three user inputs are utilized: aBUY minus SELL tolerance, a SELL minus BUY tolerance, and a SELL-to-BUYratio. For example, if a trader specifies symmetric trading as tradingconstrains, the two tolerances would be equal, and the SELL-to-BUY ratiowould be 1:1. Additionally, the SELL-to-BUY ratio can be set as cashneutral, meaning that the SELL-to-BUY ratio would be 1, ratio neutral,meaning that the SELL-to-BUY ratio would be equal to the total value ofSELL orders/the total value of BUY orders on the trade list; or theSELL-to-BUY ratio can be user defined as any number greater than zero.

According to another aspect of the present invention, as the trade listis executed, the system may adjust user specified tolerances in aneffort to balance out future executions even if the past executions havemoved the trade list toward violating the specified tolerances. Thepresent invention can be configured to take into account the currentstate of the trade list by assessing the current BUY and SELLexecutions. Equations representing the self adjusting logic are foundbelow:

New SELL Minus BUY Tolerance=Client SELL Minus BUY Tolerance−(SELLExecution Values−(SELL-to-BUY Ratio*BUY Execution Values);

New BUY Minus SELL Tolerance=Client BUY Minus SELL Tolerance+(SELLExecution Values−(SELL-to-BUY Ratio*BUY Execution Values);

Target Expected Imbalance=(−1*New SELL Minus BUY Tolerance)+(New SELLMinus BUY Tolerance+New BUY Minus SELL Tolerance)/2.

According to an embodiment of the present invention, historical andreal-time market data can be weighted appropriately to provide accurateresults. Real-time data is preferably used to sample for current day hitrates and liquidity estimation. However, real-time data for a particulartrading time period is not available from the outset of the trading timeperiod. Thus, the majority of the data at the outset of the trading timeperiod is generated from historical sources. As the trading time periodprogresses, an ever increasing real-time data set is generated for thetrading time period. As a result, the historical data that was amajority of the data used is no longer as necessary, and it is moreimportantly less accurate than the collected real-time data.

The present invention can adapt dynamically to the current environmentby using a mixture of weighted historical and real-time data. Theweights given for real-time hit rates and historical hit rates aredetermined by the amount of the trading time period that has elapsed.Thus, at the beginning of a trading period, historical data is weightedheavily, and as the trading period progresses the real-time data fromthe current day is increasingly weighted versus the historical data.This weight shift helps to provide accurate hit rates and liquidityestimation. Below are equations that illustrate the weighting principleof the auto-learning aspect of the current invention.

Hit rate for stock i in ATS j=historical hit rate for stock i in ATSj*(1−(minutes past 9:30 am/390))+(minutes past 9:30 am/390)*today's HitRate;

Avg Trade Size for stock i in ATS j=Average Avg Trade Size for stock iin ATS j*(1−(minutes past 9:30 am/390))+(timeMin/390)*today's avg tradesize.

Additionally, after the system reaches a threshold number of executionsfor a stock at an ATS, the hit rate and average trade size for stock iin ATS j is derived fully from real-time data. The following logicillustrates this principle.

Sufficient Number of Reports for ATS j=a configurable parameter

If(Number of Reports for stock i in ATS j>=Sufficient Number of Reportsfor ATS j)

{hit rate for stock i in ATS j=today's hit rate for stock i in ATS jAverage trade size for stock i in ATS j=today's average trade size forstock i in ATS j}.

According to another aspect of the present invention, trade orders canbe reallocated across ATSs in order to maximize the rate of tradeexecution and/or prevent the violation of the two user defined bounds,the BUY minus SELL tolerance and SELL minus BUY tolerance. Thisreallocation can come in the form of cancellations, corrections, neworders, or the use of reserve shares, i.e., shares not already sent toan ATS. For example, the algorithmic trading facility can be configuredto monitor execution data from all of the ATSs in which a trade orderhas been submitted. If an order is not executing in a particular ATS,the order can be reallocated to another ATS where additional liquidityexists. For example, if a complete execution occurs in one ATS, ordersin other ATSs can be cancelled and new orders can be submitted to theATS where the execution occurred. Naturally, this reallocation isdependant on the execution of the reallocated order not violating theuser defined tolerances.

For example, a BUY order for 100,000 shares of IBM is placed in ATS X,but is not executing over a period of time. As SELL orders of the tradelist execute, the trade list is over-executing to the SELL side. When aBUY order for 5,000 shares of IBM executes immediately on ATS Y, thesystem can reallocate some or all of the BUY order for 100,000 shares ofIBM from ATS X to ATS Yin an effort to execute the order and maintainneutrality.

FIG. 2 is a flow chart of an exemplary process for trading a trade listaccording to an embodiment of the present invention. At step 202, atrade request is received. For example, as described above with respectto FIG. 1, a trading client can generate and transmit to the algorithmictrading facilities a trade list or portfolio trade.

Next at step 204, trade constraints are received. As already describedabove, the trade list can be submitted along with trade constraints, thetrade constraints can be submitted separately to the algorithmic tradingfacilities, or the trade constraints can be set as predefined defaults.Corrected trade constraints are sent separate from the trade list. Tradeconstraints preferably include a neutrality constraint that defines aratio of BUYs to SELLs for a particular category, e.g., dollarneutrality, sector neutrality, etc. In such circumstances, theSELL-to-BUY ratio is typically 1; however, the trader may specify anyratio desired. The trade can further include a BUY minus SELL toleranceand/or a SELL minus BUY tolerance that define an acceptable range oramount of deviation from the neutrality constraint. For example, it maybe mathematically impossible or unlikely for an executed trade list toresult in a ratio of SELL-to-BUY to be exactly one, but the trader maystill desire for the trades to be effected even if the neutralityconstraint of one cannot be exactly met. Therefore, the trader caninclude the tolerances to allow for a defined amount of deviation fromthe neutrality constraint.

An exemplary user interface for submitting constraints according to anembodiment of the present invention is shown in FIG. 5 and is describedfurther below.

At step 206, market data is received which may include data fromreal-time feeds and historical market data. The market data can be usedfor both initial generation of trade orders as well as the dynamicupdating of the existing orders in response to real-time marketactivity.

At step 208, a plurality of trade orders are generated and transmittedto a plurality of ATSs based on at least historical market data and/orreal-time market data, the trade request received, and the tradeconstraints received. For example, as described above, the sizes, side,and destination of each trade order can be determined based onhistorical execution data for each ATS for each security. Accordingly, afirst set of trade orders can be submitted to at least one ATS in orderto effect the trade request according to the trade constraints that werereceived.

Next at step 210, each ATS being traded at is monitored for tradeexecution. As already described above, ATSs are “dark” pools and do notpublish bids and offers, however, as executions occur, information aboutexecutions returns to the submitting entity (for instance, thealgorithmic trading facility). The executions bear insight into marketconditions for each ATS, and can identify hidden liquidity. Further, asthe outstanding trade orders for a particular trade list execute orpartially execute, this execution data can be used to dynamically updatethe outstanding trade orders in order to meet the trade constraintsassociated with the trade list.

Next at step 212, trade imbalances are calculated. As already describedabove, the actual trade imbalance for the trade list is calculated basedon real-time market activity including executions relating to theoutstanding trade orders for the trade list. Further, expected tradeimbalances are also calculated as described above.

At step 214, the trade imbalances are compared against the tradeconstraints. For example, as already described above, the current tradeimbalance is compared to the user specified neutrality constraint andtolerances to determine whether outstanding trade orders need to becanceled or modified, or if new trade orders need to be generated.

If at step 216, if it is determined that the trade constraints are notmet, then at step 218 it is determined whether, and how, to reallocateorders, i.e., cancel, update, or to submit new trade orders. Forexample, as described above, the value of the list becomes higher thanthe other side, and trade orders for the side that is higher can becanceled to insure that that side does not further increase and preventsthe trade list from further exceeding constraint.

At step 220, it is checked whether the trade request is completelyfilled (i.e., all trades are complete and constraints are met). If thetrade request is not complete, then processing returns to step 206.Likewise, at step 216 if constraints were met, it is checked whether thetrade request is complete as well. Of course, if the trade request iscomplete, the processing ends.

In another embodiment of the systems and methods of the presentinvention, trade imbalances are calculated using the SELL and BUY ordersthat have not yet been executed. Thus, the equation representing thetrade imbalance and expected trade imbalance would be as shown belowrespectively:

${{{Trade}\mspace{14mu} {Imbalance}} = {{\sum\limits_{i \in {Sells}}{UnsexecutedValue}_{i}} - \left( {{SELL}\text{:}{BUY\_ Ratio}*{\sum\limits_{j \in {Buys}}{UnexecutedValue}_{j}}} \right)}},\text{}{{{Expected}\mspace{14mu} {Trade}\mspace{14mu} {Imbalance}} = {{\sum\limits_{i \in {Sells}}{ExpectedLeaveValue}_{i}} - {\left( {{SELL}\text{:}{BUY\_ Ratio}*{\sum\limits_{j \in {Buys}}{ExpectedLeaveValue}_{j}}} \right).}}}$

By using these equations, the systems and methods of the presentinvention maintain the neutrality of a trade list after neutrality hasbeen initially achieved. Further, the systems and methods of the presentinvention may switch from using the executed values to using theunexecuted values if neutrality is achieved in a trade list that wasinitially not neutral.

FIG. 3 is a flow diagram of a method for dynamically optimizing acurrently executing trade list according to an embodiment of the currentinvention. For a given trade list being traded, it is first determinedat step 302 whether the executions are close to violating user definedconstraints. If the answer is yes, then placed orders can be cancelled,as described above. If the answer is no, then processing continues tostep 306 for optimization.

At step 306, the hit rate for each security in the trade list iscalculated for each ATS. Next, at step 308, it calculates the correctsize of each security to be sent to an ATS. If the trade list iscurrently dollar neutral, and an ATS appears to have the liquidityavailable to fill the remaining shares of a particular security, allresidual shares of that security can be transmitted to that ATS.

Assignee of the present invention owns and operates a matching system(i.e., crossing destination) called POSIT (see U.S. Pat. No. 5,873,071filed on May 15, 1997, which is hereby incorporated by reference). ITGInc. also owns and operates POSIT Match, which provides scheduledmatches with concentrated liquidity throughout the trading day and inour unique after-hours cross; crosses orders at the midpoint of thebid-offer spread, resulting in significant price improvement ofexecutions; and ensures total anonymity so that trading results in nomarket impact. ITG Inc. also owns and operations POSIT Now, which offerscontinuous intra-day crossing and total anonymity; and ensures no missedtrading opportunities once orders have been submitted. POSIT Match andPOSIT Now have the capability of implementing complex constraints whileexecuting a portfolio. According to an aspect of the present invention,residual shares in the trade list can all be sent to POSIT Match orPOSIT Now along appropriate constraints at any point in the trading dayin order to complete the trade list.

Next, at step 310, the current imbalance for each ATS is calculated (asnoted above, the trade imbalance may be calculated using the unexecutedvalues of the trade list). At step 312, the portfolio can be sliced tomake two slices that are dollar neutral (or within ratio constraints).

At step 314, it is determined whether the trade list is ratio neutral.If yes, then at step 316 the entire optimization routine is performedfor a subset of the data, for each neutrality constraint, such asdollar, sector, country, etc. For example, if the neutrality constraintis “sector neutral,” then optimization is run for each sector. If no,then processing returns to step 306.

FIG. 4 is a flow diagram of an exemplary method for the construction ofa trade list that is predisposed to dollar neutrality, according to anembodiment of the present invention. At step 402, a trader adds equitynames to a trade list. The equities in a trade list are typically partof a larger portfolio. For example, a trader may use an OMS or EMS toolto begin construction of the trade list, however a separate portfoliomanagement tool might be used as well.

Once the first trade list has been assembled, at step 404 the traderenters neutrality constraints into the system. These neutralityconstraints include, but are not necessarily limited to, BUY minus SELLtolerance, SELL minus BUY tolerance, and a SELL-to-BUY ratio.

At step 406, historical market data is received and at step 408, anexpected trade imbalance is calculated, as described above, from thehistorical market data. Once the expected trade imbalance has beencalculated, it is compared to the user defined neutrality constraints atstep 410. At step 412, it is determined whether the expected tradeimbalance is within the specified tolerances. If so, the trade list issaved at step 414 and can be executed by the trader. If however, theexpected trade imbalance violates the specified constraints, the tradercan change the makeup of the trade list at step 416, and the process isrepeated until a suitable trade list is saved.

FIG. 5 is a screen shot of an exemplary interface for trading a tradelist according to an embodiment of the present invention.

Screen 500 includes a number of selections 502 for executing algorithmsfor single name trades and for list based trades. Dollar neutrality 504is a selection for implementing a list based trade wherein the resultingexecutions are dollar neutral (i.e., SELL-to-BUY ratio=1). A dollarneutral block is provided that includes a number of check boxes 506 forselecting the ATSs for participation, and a combination of fields 508for specifying trade constraints for the trade list. For example, fieldscan be included for specifying the SELL/BUY ratio, max SELL imbalanceand max BUY imbalance (in this example, as a percentage), and sectorneutrality constraints.

An interface such as that shown in screen 500 may be provided on atrading client, and provides a means by which a trade request can beprovided by the trader. Not show, the trade list can be specifiedconventionally and attached to the constraints.

Additionally, several ATSs publish information about indications ofinterest (i.e., an IOI). An IOI is not a firm order, but rather anindication that a trader is interested in making a trade. IOIs generallyinclude the name of the security, and also may include the side andamount of the potential trade. These ATSs may require a minimum shareamount to participate in the IOI matching process. The above describedsystems and methods may be used in conjunction with IOI capable ATSs.The present invention may be configured to reacting to an IOI. In thiscase, the share amount submitted for the security should not exceed thetrade constraints. If this share amount is under the minimum shareamount, as specified by the ATS, then no shares will be sent.

Additionally, several electronic communication networks (i.e., ECNs)allow a “hidden” order type. Along with displayed liquidity, there isalso non-displayed liquidity that may reside on the ECN. The presentinvention will send hidden orders to these destinations at a price ofmidpoint or better. These hidden orders are not displayed, and thusthere is no information leakage. The allocation and subsequentreallocation of these hidden orders will involve hit rates, averagetrade sizes, and processing information from the displayed liquidity onthat ECN (i.e., “level 2” data).

Some ATSs will indicate out interest without first having committedshares being sent. The present invention will utilize sending out IOIsto maximize trade executions. Furthermore, any committed shares executedduring the matching process will not exceed the list tolerances.

As briefly mentioned above, according to an embodiment of the presentinvention, a trade lists can be constructed to meet a target expectedimbalance level. Thus, when a trader desires to achieve a particularimbalance with trade list, one can be constructed so that, on average,executions occurring in the future will satisfy the trader'spreferences. In the event that one side of the trade list executesbeyond tolerance levels, a set of controls can applied.

However, the systems and methods of the present invention do not requirethat the trade list be constructed to be dollar neutral. Moreimportantly, even in situations where no predisposition to dollarneutrality exists, the systems and methods of the present invention canprovide neutrality in a forward looking predictive manner.

Thus, a number of preferred embodiments have been fully described abovewith reference to the drawing figures. Although the invention has beendescribed based upon these preferred embodiments, it would be apparentto those of skill in the art that certain modifications, variations, andalternative constructions could be made to the described embodimentswithin the spirit and scope of the invention.

1-16. (canceled)
 17. A system for automatically trading electronically alist of securities in electronic trading venues without receiving liveprice or volume data from the venues, comprising: an algorithmic tradingserver coupled via an electronic data network with at least oneelectronic trading venue that performs electronic transactions byreceiving and automatically matching electronic trade orders withouttransmitting pre-execution data regarding said received electronic tradeorders, and with a plurality of electronic trading client devices, saidalgorithmic trading server configured to receive electronically a firstelectronic message from one of said plurality of electronic tradingclient devices, said first electronic message including data relating toa transaction request to trade a list of securities, said transactionrequest including user defined constraints, and said list of securitiesincluding data identifying at least two different tradeable assets, saidalgorithmic trading server configured to generate and transmit to saidat least one electronic trading venue, automatically, a plurality ofsecond electronic messages including data relating to one or moreelectronic trade orders, based on historical trading data related tosaid destinations, said list, and said user defined constraints, saidalgorithmic trading server configured to receive execution data fromsaid at least one electronic trading venue and to identify a set ofexecuted transactions corresponding to said plurality of secondelectronic messages, to calculate an imbalance based on the set ofidentified executed transactions and said trade list, to determinewhether said imbalance exceeds said user defined constraints, and basedon said determining step, to generate at least two third electronicmessages to cancel at least a portion of one or more of said submittedelectronic trade orders in a first submitted to said at least oneelectronic trading venue and to submit a new electronic trade order to adifferent electronic trading venue.
 18. The system as recited in claim17, wherein said constraints include at least one of a BUY minus SELLtolerance, a SELL minus BUY tolerance, and a SELL-to-BUY ratio.
 19. Thesystem as recited in claim 17, said system further include historicaltrading data storage facilities for storing historical trading data fromelectronic trading venues.
 20. The system as recited in claim 17,wherein said algorithmic trading server is further coupled with areal-time market data feed and said trading data includes said real-timemarket data.
 21. The system as recited in claim 17, wherein thealgorithmic trading server if configured to calculate the imbalance by:calculating a product of said SELL-to-BUY Ratio and a total value oftrades from said identified executed trades to BUY securities;determining a total value of trades from said identified executed tradesto SELL securities; and subtracting the product from the SELL value. 22.The system as recited in claim 17, wherein the algorithmic tradingserver if configured to calculate the imbalance by calculating anexpected imbalance based on historical market data.
 23. The system asrecited in claim 22, the expected imbalance is calculated by:calculating a product of said SELL-to-BUY Ratio and a total value ofexpected orders to BUY securities from historical market data;determining a total value of expected orders to SELL securities fromhistorical market data; and subtracting the product from the totalexpected SELL value.
 24. The system as recited in claim 23, wherein thetotal expected BUY value is determined by: determining a probabilitythat an order to BUY will be present for the corresponding security, andmultiplying the probability by the average trade size of saidcorresponding security.
 25. The system as recited in claim 23, whereinthe total expected SELL side value is determined by: determining aprobability that an order to SELL will be present for the correspondingsecurity, and multiplying the probability by the average trade size ofsaid corresponding security.
 26. The system as recited in claim 18,wherein the algorithmic trading server is configured further to adjustthe SELL minus BUY tolerance based upon identified trade executions. 27.The system as recited in claim 18, wherein the algorithmic tradingserver is configured further to adjust the SELL minus BUY tolerance to anew SELL Minus BUY Tolerance=Client SELL Minus BUY Tolerance−(SELLExecutions−BUY Executions*SELL-to-BUY Ratio).
 28. The system as recitedin claim 18, wherein the algorithmic trading server is configuredfurther to adjust BUY minus SELL tolerance to equal: New BUY Minus SELLTolerance=Client BUY Minus SELL Tolerance+(SELL Executions−BUYExecutions*SELL-to-BUY Ratio).
 29. The system as recited in claim 17,wherein said trading data includes weighted real-time data andhistorical data.
 30. The system as recited in claim 17, wherein thealgorithmic trading server is configured further to reallocateunexecuted trade orders from said at least one electronic trading venueto another electronic trading venue that performs electronictransactions by automatically receiving and matching electronic tradeorders without transmitting pre-execution data regarding receivedelectronic trade orders, based on the identified executed trades. 31.The system as recited in claim 17, wherein reallocating one or more ofsaid submitted orders further includes at least one of the following:cancelling at least one of said submitted orders, correcting at leastone of said submitted orders, or the use of reserved shares.
 32. Thesystem as recited in claim 17, wherein calculating a trade imbalancefurther includes: identifying unexecuted trades by finding thedifference of said trade list and said executed trades; and calculatinga trade imbalance based on said unexecuted trades and said trade list.